218-1 Optimizing Corn Plant Density.

See more from this Division: C03 Crop Ecology, Management and Quality
See more from this Session: Crop Ecology, Management and Quality Oral

Tuesday, November 8, 2016: 9:30 AM
Phoenix Convention Center North, Room 121 C

Emerson D. Nafziger, Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL
Abstract:
While input rate studies have long formed the basis for determining optimal input rates, there has not been much consistency in how such data are used to formulate rates that maximize economic return. Using an approach similar to that employed in the Nitrogen Rate Calculator in use in the U.S. Corn Belt, we fit an appropriate function to yields for each of 27 corn (Zea mays L.) plant density trials conducted over a four-year period in Illinois, then calculated the predicted return to seed (RTS = yield x price per unit of grain – seeding rate x cost per unit of seed) over the range of seeding rates for each response. These values were averaged across the set of curves to give an RTS response curve, the maximum of which is the density producing the maximum RTS. Among individual sites, the optimum plant density ranged from 59,000 to 100,000 plants per hectare. The density providing the maximum RTS across sites was 82,000 plants per hectare, which produced a RTS of $1,770 per hectare. We used the same set of response data in a simulation designed to test the effect of varying plant density across a field. Despite the wide range of optima among sites, establishing the optimum density within each of the 27 “sections” of the field (that is, variable-rate seeding) compared to using the overall optimum density for the entire field increased the RTS for the field by only $6.74 per hectare, saving 570 seeds ($1.71) and producing 34 kg more yield ($5.03) per hectare. Based on these data, variable-rate seeding would produce a profit only if done at little or no cost.

See more from this Division: C03 Crop Ecology, Management and Quality
See more from this Session: Crop Ecology, Management and Quality Oral

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